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PRWP

Reproducibility package for Lives, Livelihoods, and Learning: A Global Perspective on the Wellbeing Impacts of the COVID-19 Pandemic

2024
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Reference ID
RR_WLD_2024_74-v03
DOI
https://doi.org/10.60572/zn4g-3h04
Author(s)
Benoit Decerf, Jed Friedman, Arthur Mendes, Steven Pennings, Nishant Yonzan
Collections
World Bank Policy Research Working Papers
Metadata
JSON
Created on
Mar 20, 2024
Last modified
Mar 20, 2024
  • Project Description
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  • Citation
  • Overview

    Abstract

    This study compares the magnitude of the losses that the COVID-19 pandemic inflicted across three critical dimensions: loss of life, loss of income, and loss of learning. The wellbeing consequences of excess mortality are expressed in years of life lost while those of income losses and school closures are expressed in additional years spent in poverty (as measured by national poverty lines), either currently or in the future. While the 2020-2021 period witnessed a global drop in life expectancy and the largest one-year increase in global poverty in many decades, widespread school closure may cause an increase in future poverty almost twice as large. The estimates of wellbeing loss for the average global citizen include a loss of almost 3 weeks of life (19 days), an additional two and half weeks spent in poverty in the years 2020 and 2021 (17 days), and the possibility of an additional month of life in poverty in the future due to school closures (31 days). Wellbeing losses are also not equitably distributed across countries. The typical high-income country suffered more total years of life lost than additional years in poverty, while the opposite holds for the typical low- or middle-income country. Aggregating total losses requires a valuation for a year of life lost vis-à-vis an additional year spent in poverty. If a year of life lost is valued at six or fewer additional years spent in poverty, low-income countries suffered greater total wellbeing loss than high-income countries. However, for a wide range of valuations, the greatest wellbeing losses fell on upper-middle-income countries and for countries in the Latin America region. This set of countries suffered the largest mortality costs as well as large losses in learning and sharp increases in poverty.

    Reproducibility Package

    Scripts
    Readme Get Reproducibility Package
    Link: https://reproducibility.worldbank.org/index.php/catalog/116/download/305/README.pdf
    Reproducibility package (code and partial data) for Lives, Livelihoods, and Learning: A Global Perspective on the Well-being Impacts of the Covid-19 Pandemic
    Title
    Reproducibility package (code and partial data) for Lives, Livelihoods, and Learning: A Global Perspective on the Well-being Impacts of the Covid-19 Pandemic
    Date
    2024-02
    Dependencies
    All dependencies are stored in the folder "DoFiles/ado"
    Instructions
    See README in reproducibility package
    Notes
    Computational reproducibility verified by Development Impact (DIME) Analytics team, World Bank
    Source code repository
    Repository name URI
    Reproducible Research Repository (World Bank) https://reproducibility.worldbank.org
    Software
    Stata
    Name
    Stata
    Version
    17

    Reproducibility

    Technology environment

    The code was run in a computer with the following specifications:

    • OS: Windows 10 Enterprise, version 21H2
    • Processor: Intel(R) Xeon(R) CPU E7-4890 v2 @ 2.80GHz 2.80 GHz
    • Memory available: 5.9 GB
    • Software version: Stata 17
    Technology requirements

    Runtime: 40 minutes

    Data

    Datasets
    WHO Estimates of Excess Mortality Associated With COVID-19 Pandemic
    Name
    WHO Estimates of Excess Mortality Associated With COVID-19 Pandemic
    Note
    WHO dataset on global excess deaths, used to create YLL. Data was accessed on May 2022. Please refer to “Previous releases” at the bottom of the website provided to download the May 2022 vintage. Download is a zip file. Excel file used is "WHO_COVID_Excess_Deaths_EstimatesByCountry.xlsx", only the tab Country by year, sex and age. Please delete rows 1 to 11, rows 5434 to 5439, and change the file name to "Excess deaths WHO.xlsx".
    Access policy
    Data is public and included in the reproducibility package
    Data URL
    https://www.who.int/data/sets/global-excess-deaths-associated-with-covid-19-modelled-estimates
    Country-level Mortality data from: "Too Young to Die": Deprivation Measures Combining Poverty and Premature Mortality"
    Name
    Country-level Mortality data from: "Too Young to Die": Deprivation Measures Combining Poverty and Premature Mortality"
    Note
    Mortality data, used to create YLL. No cleaning took place. Data was accessed on February 2023. Dataset can be found inside the folder Replication/Data/GBD in the Data URL with the name IHME-GBD_2017_DATA-f89cefb0-1.csv.
    Access policy
    Data is public and included in the reproducibility package
    Data URL
    https://www.openicpsr.org/openicpsr/project/119941/version/V1/view
    Historical country income group classification from Daniel Mahler
    Name
    Historical country income group classification from Daniel Mahler
    Note
    Historical country income group classification. No cleaning took place. Dataset was accessed on November 2023. Dataset can be found inside the folder OutputData of the Data URL, in a file named CLASS.dta. Please change its name to CLASS_historical.dta
    Access policy
    Data is public and included in the reproducibility package
    Data URL
    https://github.com/PovcalNet-Team/Class
    Global binned income distribution per country and year from: The Impact of COVID-19 on Global Inequality and Poverty
    Name
    Global binned income distribution per country and year from: The Impact of COVID-19 on Global Inequality and Poverty
    Note
    Global binned income distribution per country and year. Version accessed was 20230919_2017_01_02_PROD. To generate the database, run the do files of the Data URL. This code queries updated poverty lines from the Poverty and Inequality Platform (PIP, World Bank) publicly available at https://pip.worldbank.org/home. If the code provided produces updated data that differs from the data used in this paper, please refer to the dataset authors. After running the code, change the name of the variable region_code to region_pip, and obs to quantile and save the dataset as GlobalDist_1000bins_2019-2023_sep23.dta
    Access policy
    Data is public and included in the reproducibility package
    Data URL
    https://github.com/worldbank/covid-impact-on-inequality-and-poverty/tree/main
    Welfare vectors from: The Impact of COVID-19 on Global Inequality and Poverty
    Name
    Welfare vectors from: The Impact of COVID-19 on Global Inequality and Poverty
    Note
    Welfare vectors, used to create CPY. No cleaning took place. Version accessed was 20230919_2017_01_02_PROD.
    Access policy
    Dataset is restricted. Replicators seeking to access the data should contact the authors of "The Impact of COVID-19 on Global Inequality and Poverty" (World Bank Policy Research Working Paper 10198, http://hdl.handle.net/10986/38114). Dataset file name is "GlobalDist_1000bins_MYLseptember23_limitedvars.dta" in the code reading the data. The data is not included in the reproducibility package.
    World Economic Outlook (WEO) database by the International Monetary Fund
    Name
    World Economic Outlook (WEO) database by the International Monetary Fund
    Note
    WEO Database, macroeconomic data series produced by the International Monetary Fund. Dataset was accessed in October 2022. Please click on the button “By Countries” to download the dataset and name it WEOOct2022all.xls.
    Access policy
    Data is public and included in the reproducibility package
    Data URL
    https://www.imf.org/en/Publications/WEO/weo-database/2022/October/download-entire-database
    World Bank's World Development Indicators (WDI) Database
    Name
    World Bank's World Development Indicators (WDI) Database
    Note
    World Bank's WDI. Dataset was accessed in September 2023. Click on “CSV download” under Bulk Downloads in the Data URL . Open WDI_CSV.zip. Change the name of WDIData.csv to WDIEXCEL_extracted0923.csv
    Access policy
    Data is public and included in the reproducibility package
    Data URL
    https://datatopics.worldbank.org/world-development-indicators/
    Penn World Table 10.01
    Name
    Penn World Table 10.01
    Note
    PWT version 10.01 is a database with information on relative levels of income, output, input and productivity, covering 183 countries between 1950 and 2019. We use data from PWT 10 to calibrate the labor share, initial capital to output ratio, depreciation rate and TFP. Labor share: The labor share is a key parameter for the impact of human capital on growth and is taken from Penn World Table 10 (PWT10) for 2019 (most recent observation) under “labsh” “Share of labour compensation in GDP at current national prices”. Depreciation rate is taken from “delta” the “average depreciation rate of the capital stock”. Initial capital-to-GDP ratio: The initial capital-to-GDP ratio is calculated using the 2019 observations on physical capital stock and GDP from PWT 10. More specifically, we compute KY= rnna/rgdpna where “rnna” is “Capital stock at constant 2017 national prices (in mil. 2017US$)” and “rgdpna” is “Real GDP at constant 2017 national prices (in mil. 2017US$)”. These data was copied to columns G, H, I of the tab "Summary" of the file OUTPUT_default_nolinks_31March2023.xlsx.
    Access policy
    Data is public and included in the reproducibility package
    Data URL
    https://www.rug.nl/ggdc/productivity/pwt/?lang=en
    Total investment from the World Economic Outlook report for October 2022
    Name
    Total investment from the World Economic Outlook report for October 2022
    Note
    Total investment by country for 2020-2027, expressed as a ratio of total investment in current local currency and GDP in current local currency was taken from the IMF's World Economic Outlook report for October 2022. The corresponding variable name in the original data is “NID_NGDP”. Data was copied and pasted manually in columns AR-AY (2020-2027) of the tab "WEO_investment" in the file OUTPUT_default_nolinks_31March2023.xlsx.
    Access policy
    Data is public and included in the reproducibility package
    Data URL
    https://www.imf.org/en/Publications/WEO/Issues/2022/10/11/world-economic-outlook-october-2022
    World Bank’s Human Capital Project
    Name
    World Bank’s Human Capital Project
    Note
    The data for the HCI of young cohorts (5-19 year-olds in 2020-2021 and future cohorts) are taken from the World Bank’s Human Capital Project, (which measures the expected LAYS a child born today is expected to attain by her 18th birthday, including quantity and quality of education, S_c and Q_c). The HCI data can be downloaded in the Data URL provided under “Expected Years of School” and “Test Scores”. Data was copied and pasted manually in columns J and K of the tab "Summary" in the file OUTPUT_default_nolinks_31March2023.xlsx.
    Access policy
    Data is public and included in the reproducibility package
    Data URL
    https://www.worldbank.org/en/publication/human-capital
    Barro-Lee Educational Attainment Database
    Name
    Barro-Lee Educational Attainment Database
    Note
    Data for the years of schooling of older generations is from the Barro-Lee Educational Attainment Database. Data was copied and pasted manually in column E of the tab "BARROLEE" in the file OUTPUT_default_nolinks_31March2023.xlsx.
    Access policy
    Data is public and included in the reproducibility package
    Data URL
    http://www.barrolee.com
    National Accounts Data from the UN’s Statistical Division (UNSD)
    Name
    National Accounts Data from the UN’s Statistical Division (UNSD)
    Note
    Data as of January 2024 on the share of agriculture in total Gross Value Added reported by the UNSD was used to simulate future total factor productivity (TFP) growth paths. We used the ISIC3 classification of economic activities. The data can be downloaded in the link below under National Accounts Estimates of Main Aggregates, variable “Gross Value Added by kind of Economic Activity at current prices”. Data was copied and manually pasted in column C of the tab "Data_agriculture" in the file OUTPUT_default_nolinks_31March2023.xlsx.
    Access policy
    Data is public and included in the reproducibility package
    Data URL
    http://data.un.org/Explorer.aspx?d=SNAAMA
    UN’s World Population Prospects
    Name
    UN’s World Population Prospects
    Note
    We use the UN’s World Population Prospects forecasts for total population growth and the working-age population from 2021 to 2100. The forecasts for total population growth from 2021 to 2100 were downloaded from https://population.un.org/wpp/Download/Standard/MostUsed/ and manually pasted to column G of the tab "Data_agriculture" in the file OUTPUT_default_nolinks_31March2023.xlsx. The forecasts for working-age population from 2021 to 2100 were downloaded from https://population.un.org/wpp/Download/Standard/Population/ and manually pasted to column H of the same tab.
    Access policy
    Data is public and included in the reproducibility package
    Data URL
    https://population.un.org/wpp/
    World Bank’s World Development Indicators (WDI) - GDP per capita and labor force participation
    Name
    World Bank’s World Development Indicators (WDI) - GDP per capita and labor force participation
    Note
    The labor force participation rate is taken from the World Bank’s WDI under “Labor force participation rate, total (% of total population ages 15-64) (modeled ILO estimate)”, code SL.TLF.ACTI.ZS, and was manually copied to column E of the tab "WDI" in the file OUTPUT_default_nolinks_31March2023.xlsx. GDP per capita is taken from the WDI under “GDP per capita, constant 2015 US$” code NY.GDP.PCAP.KD., and was manually copied to column D of the same tab.
    Access policy
    Data is public and included in the reproducibility package
    Data URL
    https://datatopics.worldbank.org/world-development-indicators/
    Global Monitoring of School Closures Caused by the COVID-19 Pandemic from UNESCO
    Name
    Global Monitoring of School Closures Caused by the COVID-19 Pandemic from UNESCO
    Note
    The UNESCO data records for each day of 2020 and 2021 whether schools are fully closed, partially closed, or open. UNESCO codes days into “Fully Closed” and “Partially Closed” with the latter getting a weight of 0.5. You can download variables Fully Closed” and “Partially Closed” at UNESCO’s dashboard on the global monitoring of school closures caused by the COVID-19 pandemic. Data was manually pasted to the column C of the tab "UNESCO-COVID" in the file OUTPUT_default_nolinks_31March2023.xlsx.
    Access policy
    Data is public and included in the reproducibility package
    Data URL
    https://covid19.uis.unesco.org/global-monitoring-school-closures-covid19/
    Data statement

    All datasets used are public and included in the reproducibility package except for the Welfare Vectors dataset. Replicators can contact the dataset authors (specified in the datasets section) for access.

    Description

    Output
    Lives, Livelihoods, and Learning: A Global Perspective on the Wellbeing Impacts of the COVID-19 Pandemic
    Type
    Working paper
    Title
    Lives, Livelihoods, and Learning: A Global Perspective on the Wellbeing Impacts of the COVID-19 Pandemic
    Authors
    Benoit Decerf, Jed Friedman, Arthur Mendes, Steven Pennings, Nishant Yonzan
    Description
    Policy Research Working Paper (PRWP)
    Authors
    Author Affiliation Email
    Benoit Decerf World Bank bdecerf@worldbank.org
    Jed Friedman World Bank jfriedman@worldbank.org
    Arthur Mendes World Bank agalegomendes@worldbank.org
    Steven Pennings World Bank spennings@worldbank.org
    Nishant Yonzan World Bank nyonzan@worldbank.org
    Date of production

    2024-02

    Scope and coverage

    Geographic locations
    Location Code
    World WLD
    Keywords
    covid welfare poverty mortality learning
    Topics
    ID Topic Vocabulary Vocabulary URI
    D63 Equity, Justice, Inequality, and Other Normative Criteria and Measurement Journal of Economic Literature (JEL)
    I15 Health and Economic Development Journal of Economic Literature (JEL)
    I31 General Welfare, Well-Being Journal of Economic Literature (JEL)
    I32 Measurement and Analysis of Poverty Journal of Economic Literature (JEL)
    O15 Human Resources • Human Development • Income Distribution • Migration Journal of Economic Literature (JEL)

    Disclaimer

    Disclaimer

    The materials in the reproducibility packages are distributed as they were prepared by the staff of the International Bank for Reconstruction and Development/The World Bank. The findings, interpretations, and conclusions expressed in this event do not necessarily reflect the views of the World Bank, the Executive Directors of the World Bank, or the governments they represent. The World Bank does not guarantee the accuracy of the materials included in the reproducibility package.

    Access and rights

    License
    Name URI
    Modified BSD3 https://opensource.org/license/bsd-3-clause/

    Contacts

    Contacts
    Name Affiliation Email
    Benoit Decerf World Bank bdecerf@worldbank.org
    Reproducibility WB World Bank reproducibility@worldbank.org

    Information on metadata

    Producers
    Name Abbreviation Affiliation Role
    Reproducibility WBG DIME World Bank - Development Impact Department Verification and preparation of metadata
    Date of Production

    2024-02-26

    Document version

    1

    Citation

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